Super resolution techniques provide a way to take original, low resolution images and generate images having a higher resolution. These techniques may use multiple frames or single frames of low resolution images. Single frame super resolution techniques include self-similarity super resolution (SSSR), in which similarities across a single frame of a low resolution image are exploited to generate the higher resolution images.
SSSR generally performs well to recover high frequency detail and keep sharpness of edges after image upscaling, including graphics-based images. Graphics image data may consist of simple pixel structures such as lines, characters, rectangles, circles, icons, cartoons, etc. These structures have regular and non-random shapes and possess sufficient self-similarities across different scales making them appropriate for SSSR processing.
However, upscaling of graphics images using SSSR often results in annoying artifacts. One such artifact comes from ‘over filtering,’ also referred to as overshooting, that causes an artifact called ringing, in which rings near strong or sharp edges and non-uniform color or gray patches appear in the resulting high resolution image. Graphics do not completely follow to the basic image model of common video. For typical video, the low resolution images are generated by convolving its corresponding high resolution image with a low pass filter and then down sampling it. One example is the optical blur filter placed on top of image sensors when capturing the low resolution image. The input low resolution graphics usually have very sharp edges like step signals with very little transition or blurring.
It is often not possible to determine at the super resolution stage of processing whether or not the input follows the basic imaging model or not. This results in super resolution upscaling results that are similar or even worse than other scaling approaches. However, it is possible to preserve the monotonicity in the normal direction and homogeneity in the edge direction. Effectively remove the artifacts mentioned above for each color channel after the SSSR or other scaling process.